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      Fiji: an open-source platform for biological-image analysis

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

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          Computer control of microscopes using µManager.

          Arthur Edelstein, Nenad Amodaj, Karl Hoover … (2010)
          With the advent of digital cameras and motorization of mechanical components, computer control of microscopes has become increasingly important. Software for microscope image acquisition should not only be easy to use, but also enable and encourage novel approaches. The open-source software package µManager aims to fulfill those goals. This unit provides step-by-step protocols describing how to get started working with µManager, as well as some starting points for advanced use of the software. © 2010 by John Wiley & Sons, Inc.
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            Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy.

            Philipp Keller, Annette Schmidt, Joachim Wittbrodt … (2008)
            A long-standing goal of biology is to map the behavior of all cells during vertebrate embryogenesis. We developed digital scanned laser light sheet fluorescence microscopy and recorded nuclei localization and movement in entire wild-type and mutant zebrafish embryos over the first 24 hours of development. Multiview in vivo imaging at 1.5 billion voxels per minute provides "digital embryos," that is, comprehensive databases of cell positions, divisions, and migratory tracks. Our analysis of global cell division patterns reveals a maternally defined initial morphodynamic symmetry break, which identifies the embryonic body axis. We further derive a model of germ layer formation and show that the mesendoderm forms from one-third of the embryo's cells in a single event. Our digital embryos, with 55 million nucleus entries, are provided as a resource.
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              Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.

              Christian Conrad, Catherine Chapuis, Rolf Kabbe … (2010)
              Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.
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                Author and article information

                Journal
                Title: Nature Methods
                Abbreviated Title: Nat Methods
                Publisher: Springer Science and Business Media LLC
                ISSN (Print): 1548-7091
                ISSN (Electronic): 1548-7105
                Publication date Created: July 2012
                Publication date (Electronic): June 28 2012
                Publication date (Print): July 2012
                Volume: 9
                Issue: 7
                Pages: 676-682
                Article
                DOI: 10.1038/nmeth.2019
                PMC ID: 3855844
                PubMed ID: 22743772
                SO-VID: 0d2218d8-10aa-46cd-b82b-ed05c0b7cf81
                Copyright © © 2012
                License:

                http://www.springer.com/tdm

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